评估数据质量对基于智能手机的户外6MWT距离估计的影响
Sara Caramaschi1, Carl Magnus Olsson1, Elizabeth Orchard2
1Department of Computer Science and Media Technology, Internet of Things and People Research Center, Malmö University, 21119 Malmö, Sweden.
Sensors (Basel, Switzerland)
|April 27, 2024
概括
使用全球导航卫星系统 (GNSS) 数据进行远程功能能力评估需要进行质量控制. 本研究开发了识别不可靠的GNSS信号的方法,确保临床医生和患者获得准确的远程测试结果.
科学领域:
- 生物医学工程 生物医学工程
- 医疗信息学 医疗信息学
- 康复技术 康复技术 康复技术
背景情况:
- 技术进步使得远程功能能力评估成为可能,比如6分钟步行测试.
- 当前的远程评估研究往往忽视了数据质量,特别是在具有挑战性的现实条件下.
- 全球导航卫星系统 (GNSS) 信号质量不佳可能会损害远程测试中距离测量的可靠性.
研究的目的:
- 调查过规则对GNSS定位数据的影响,以便在远程功能能力评估中准确计算距离.
- 开发和评估基于GNSS信号特征评估距离估计可靠性的方法.
- 为了提高远程功能能力测试结果的可靠性,用于临床使用.
主要方法:
- 从定位数据计算行走距离的常用算法应用过规则,以减轻噪音样本.
- 利用后勤回归来评估基于GNSS信号特征的距离估计可靠性.
- 执行基于错误的分析 (估计距离错误) 和基于用户的分析 (区分传统和非传统测试).
- 评估了与步行路径不规则性和方向变化相关的特征,用于数据质量评估.
主要成果:
- 证明了过规则在提高从噪音高的GNSS数据计算距离的准确性方面的影响.
- 在二进制分类任务中实现了高性能,用于识别不可靠的测试,达到0.93的F1得分和0.97的曲线下面面积 (AUC) 以用户为基础的分类.
- 强调了路径不规则性和方向变化特征在确定数据质量的重要性.
结论:
- 过噪音GNSS样本对于可靠的远程功能能力评估至关重要.
- 基于信号特征的强有力的测试可靠性分类方法可以显著提高数据质量.
- 为临床医生提供质量评估,为患者提供重复不可靠测试的机会,可以提高远程功能能力监测的整体效用和准确性.
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